Plant genetic diversity affects multiple trophic levels and trophic interactions

Intraspecific genetic diversity is an important component of biodiversity. A substantial body of evidence has demonstrated positive effects of plant genetic diversity on plant performance. However, it has remained unclear whether plant genetic diversity generally increases plant performance by reducing the pressure of plant antagonists across trophic levels for different plant life forms, ecosystems and climatic zones. Here, we analyse 4702 effect sizes reported in 413 studies that consider effects of plant genetic diversity on trophic groups and their interactions. We found that that increasing plant genetic diversity decreased the performance of plant antagonists including invertebrate herbivores, weeds, plant-feeding nematodes and plant diseases, while increasing the performance of plants and natural enemies of herbivores. Structural equation modelling indicated that plant genetic diversity increased plant performance partly by reducing plant antagonist pressure. These results reveal that plant genetic diversity often influences multiple trophic levels in ways that enhance natural pest control in managed ecosystems and consumer control of plants in natural ecosystems for sustainable plant production.

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Study description
Research sample Sampling strategy

Data collection
Timing and spatial scale

Data exclusions
All data needed to evaluate the conclusions in the paper are present in the paper and the Supplementary Information. The raw and processed data used in this study is available in the Supplementary Files (Supplementary Data 1) and is deposited to Zenodo: https://zenodo.org/record/7302775#.Y2tz8MhzmLk. The code used to analyse data is deposited to Zenodo: https://zenodo.org/record/7307292#.Y2tzsMhzmLl.
We conducted a literature search on the Web of Science and China National Knowledge Internet (www.cnki.net) (last accessed in September 2021) using the Boolean search string: ["plant genetic diversity" OR "plant genotypic diversity" OR "crop genetic diversity" OR "crop genotypic diversity" OR "intraspecific diversity" OR "inter-genotypic" OR "intervarietal" OR "resistant *susceptible cultivar*" OR "pure * mixed cultivar" OR "cultivar mixture" OR "varietal mixture"] AND ["predat*" OR "herbivor*" OR "parasitoid" OR "wasp*" OR "natural enem*" OR "pest management" OR "pest control" OR "biological control" OR "plant disease" OR "plant virus" OR "nematode" OR "weed" OR "yield" OR "productivity" OR "biomass"]. Overall, about 145000 papers were screened for relevance and 413 were finally selected. Means, standard errors (or standard deviations), and sample sizes of the selected variables could be extracted from tables, figures, the main text or supporting information. Data extraction from figures was conducted with Get Data Graph Digitizer 2.25. When we obtained the data, we analyzed the effect size of response to plant genetic diversity for trophic groups, the effect of plant genetic diversity on bi-trophic/tri-trophic associations and finally analyzed the effect of plant genetic diversity across trophic levels.
We followed the PRISMA protocols for study selection and inclusion in the systematic meta-analysis. We collected data from Web of Science and China National Knowledge Internet (www.cnki.net), finally we collected 4702 observations from 413 studies to study the effects of plant genetic diversity on multiple trophic groups (i.e., plants, plant antagonists, invertebrate herbivores, weeds, plantfeeding nematodes, plant diseases and natural enemies of herbivores). In addition, 1484 interactive effect sizes derived from 139 studies were used to test the effects of plant genetic diversity on the bi-trophic interactions between plant antagonist and plant performances, and 91 interactive effect sizes derived from 13 studies were used to test the effects of plant genetic diversity on the tri-trophic interactions among natural enemies, herbivores and plant performances.
With the aim of constructing a comprehensive database, we tried to collect as many as experiments that fulfill our criteria (described below). About 145000 papers were reviewed for relevance and 413 were finally selected based on the following criteria: (1) the study included at least one comparison between plant stands with one genotype (monoculture control treatment) or 2 genotypes (mixed treatment); (2) the use of pesticides and other practices (fertilizer, irrigation, etc) should be the same for the control and mixed treatments; (3) both the control and the mixed treatment had one and the same plant species; (4) the measurements of treatment and control groups were performed at the same spatiotemporal scale; (5) when a study covered multiple levels of plant genotypes, measurements of monoculture stands and different numbers of plant genotypes were recognized as independent observations; and (6) when a study included different levels of plant species addition, measurements for each plant species addition level were considered to be independent observations. Data extraction from figures was conducted with Get Data Graph Digitizer 2.25. We first used the data for which the authors in a cited paper had listed the mean values of multiple sampling dates or multiple sampling years. If the authors did not present these mean values, we adopted the data of the latest sampling date.
First, we selected the papers through a search on the Web of Science and China National Knowledge Internet (www.cnki.net) (last accessed in September 2021), and then extracted the data from the papers. Second, we established a datasheet for trophic groups (invertebrate herbivores, weeds, plant-feeding nematodes, plant diseases, plant antagonist, predators, parasitoids and plants). In this datasheet, we included weed diversity, weed growth, herbivore abundance, herbivore diversity, herbivore damage, disease spread, disease damage, nematode abundance, predator abundance, predator diversity, parasitoid abundance, parasitoid diversity, parasitism, plant growth, plant reproduction, plant quality, plant antagonist intensity and plant antagonist diversity. Nian-Feng Wan and Liwan Fu recorded the data which were recorded in Excel.
The deadline for collecting data is September 2021 (searches were performed in Web of Science and China National Knowledge Internet between July and September 2021). Searches included globally published studies but were limited to those published in English and Chinese.
When we collected the data, the data were excluded in this meta-analysis if they did not conform to the following criteria: (1) the